Neuronal gating of tactile input and sleep in 10-month-old infants at typical and elevated likelihood for autism spectrum disorder

Sleep problems in Autism Spectrum Disorder (ASD) emerge early in development, yet the origin remains unclear. Here, we characterise developmental trajectories in sleep onset latency (SOL) and night awakenings in infants at elevated likelihood (EL) for ASD (who have an older sibling with ASD) and infants at typical likelihood (TL) for ASD. Further, we test whether the ability to gate tactile input, using an EEG tactile suppression index (TSI), associates with variation in SOL and night awakenings. Parent-reported night awakenings and SOL from 124 infants (97 at EL for ASD) at 5, 10 and 14 months were analyzed using generalized estimating equations. Compared to TL infants, infants at EL had significantly more awakenings and longer SOL at 10 and 14 months. The TSI predicted SOL concurrently at 10 months, independent of ASD likelihood status, but not longitudinally at 14 months. The TSI did not predict night awakenings concurrently or longitudinally. These results imply that infants at EL for ASD wake up more frequently during the night and take longer to fall asleep from 10 months of age. At 10 months, sensory gating predicts SOL, but not night awakenings, suggesting sensory gating differentially affects neural mechanisms of sleep initiation and maintenance.


Methods and materials
Participants. One hundred and twenty four infants took part in a longitudinal study running from 2013 to 2019 at 5, 10, and 14 months. The experimental protocol was approved by the National Research Ethics Service (13/LO/0751) and the Research Ethics Committee of the Department of Psychological Sciences, Birkbeck, University of London (13/1617). All experiments were performed in accordance with relevant guidelines and regulations. Parents provided informed, written consent before the onset of the study. The study recruited participants with a first degree relative with ASD and/or ADHD. As the focus of the current study is understanding ASD-related atypicalities in sensory processing and sleep, infants with a family history of only ADHD were not included. Participants were classified as infants at EL for ASD if they had a first-degree relative diagnosed with ASD by a licensed clinician (n = 97, female = 45). Infants with no first-degree relatives with an ASD diagnosis and a typically developing older sibling were classified as infants at TL for ASD (n = 27, female = 9). Infants at TL were recruited from a volunteer database at the Centre for Brain Tables 1  and S1).

Measures. Sleep measures.
Questions from the Sleep and Settle Questionnaire (SSQ; 31) were used as measures for sleep onset latency and the number of awakenings. The number of awakenings indicates the number of times the infant woke up during the night on average in the preceding week. Integers were required for analysis of this ordinal variable (see Analytical approach), therefore where parents filled in a range instead of one number, the average was taken and, in case of a non-integer, the value was truncated (e.g. 2.5 would become 2). Parents reported separately on the time it took to settle their infant for day (5am to 6 pm), evening (6 pm to 10 pm) and night sleeps (10 pm to 5am), again, with an average estimate over the preceding week. If parents reported a range, the mean was taken. We averaged day, evening and night values to create a continuous sleep onset latency measure. Participants were also included if they only filled in one or two of the questions, since not all infants take two additional naps. However, this was less than 10% of the total participants included in the calculation of sleep onset latency at all three visits.
ASD diagnosis. At 3 years, infants at EL were assigned a best estimate research diagnosis ASD (EL-ASD +) or non-autism (EL-ASD-) according to the DSM-5 diagnostic criteria by experienced researchers with the help of a licensed clinical psychologist (GP and TC

EEG Paradigm.
A full description is reported in Piccardi et al. 34 .
Stimuli. Custom built voice coil tactors were attached to the bare soles of each foot of the infant with cohesive tape. Vibrotactile stimuli were delivered to both feet simultaneously with a frequency of 220 Hz. Stimuli lasted 200 ms and were consistently presented in pairs (S1-S2) with a 500 ms interstimulus interval (Fig. 1). The time between pairs of stimuli, the intertrial interval, varied randomly between 8 and 12 s. In total, 38 pairs of stimuli were administered split across two 4 min blocks with a 2 min break in between. As a distraction, a visually engag-   www.nature.com/scientificreports/ ing cartoon without language content (Fantasia by Walt Disney) was played during the experiment. Infants were seated on the lap of the parent 60 cm from the screen in a dimly illuminated room.
Apparatus and time-frequency analysis of EEG. EEG was recorded using 124 channels of a 128-channel HydroCel Geodesic Sensor Net connected to a NetAmps 400 amplifier (Electrical Geodesic, Eugene, OR) and referenced online to the vertex (Cz). Net station (Electrical Geodesic) was used to pre-process the EEG data offline. If individual epochs exhibited voltage changes over 200 µV in one segment (identified by automated artifact detection), individual channels within segments were eliminated after additional visual inspection. Artifact free EEG segments were processed and analysed using EEGLAB (v.13.4.3b) in MATLAB®. Spectral decompositions were conducted using Wtools (developed by E. Parise, L. Filippin, & G. Csibra, available upon request), employing complex Morlet wavelets 3-20 Hz with 1 Hz resolution. A continuous wavelet transformation of all segments was conducted, and the absolute value of the results was extracted. A 100 ms pre-stimulus window was used as a baseline. Individual epochs were averaged per participant. Time-frequency decomposition was used to quantify oscillatory alpha amplitude desynchronization to tactile stimulation (i.e. 6-10-Hz alpha amplitude during the task as compared to alpha amplitude at baseline). The average 6-10-Hz alpha desynchronization oscillatory amplitude was extracted from two 500-ms-long windows time-locked to S1 and S2 offset. A tactile suppression index (TSI) was computed by subtracting alpha amplitude desynchronization at S2 from alpha amplitude desynchronization at S1.
Analytical approach. Statistical analysis was performed in SPSS v25. Three values of sleep onset latency (2 EL; 1 TL), one value of the number of awakenings (TL) and one value of the TSI (EL) were more than three standard deviations above the mean and trimmed to one integer above the highest value. To analyse the trajectory of sleep onset latency and the number of awakenings, generalized estimating equations (GEE) were used factoring in Group and time of the measurement (Visit). GEE was chosen to model the non-normal response variables and to accommodate for missing data. For number of awakenings, a count variable, a Poisson distribution with a log-link was specified. Due to a right skew for the sleep onset latency variable (see Table S2 for skewness and normality), a gamma distribution with log-link was specified. An integer of 1 was added to the sleep onset latency variable, so values of zero would not be omitted in the GEE. Maximum likelihood was selected for scale parameter estimation. The structure of the working correlation matrix was specified as 'unstructured' with a robust estimator.
To assess the main effects of Visit (5, 10 and 14 months) and Group (EL and TL), the GEE was run with main effects only and then a Group*Visit interaction was added in a separate step, from which the interaction terms is ascertained. Post hoc Bonferroni corrected pairwise comparisons were run for significant main effects of Visit. In case of a significant interaction with Visit, a separate GEE was run per timepoint to assess group differences. GEE models were run to test whether the TSI was associated with the sleep parameters, first concurrently (i.e. at 10 months), then longitudinally. To test the generalisability of results across the EL group, all analyses were repeated after the removing infants who were subsequently diagnosed with ASD at 36 months. We also excluded infants at EL who did not come in to the 36 month assessment and therefore could not be assigned to EL-ASD + nor EL-ASD-.
Looking at the sleep trajectory by group (see Fig. 2), the number of awakenings (Waldχ 2 = 13.239, p = 0.001) and sleep onset latency (Waldχ 2 = 15.272, p < 0.001) significantly decreased with age in infants at TL, while in infants at EL they remained stable over time (Waldχ 2 = 1.753, p = 0.416 and Waldχ 2 = 3.787, p = 0.151, respectively). In TL infants, post hoc tests indicated that the number of awakenings was significantly higher at 5 months  Table S3 for descriptives).
When the sleep trajectory analyses were re-run by splitting the data in groups based on ASD outcome (TL vs EL-ASD-and TL vs EL-ASD +), the small EL-ASD + group (n = 12) tended to have the most extreme values. In Associations with tactile repetition suppression. Scores on the TSI were significantly higher (decreased attenuation of response with repetition) in infants at TL compared to infants at EL (t = 2.717 (66), p = 0.008) in line with results previously reported by Piccardi et al. 25 in infants from the same cohort (Table 1). Summary correlations between TSI and sleep measures at 10 and 14 months are presented in Table 2. To test whether emerging sleep problems associate with the TSI concurrently, two GEE models were run, one with the number of awakenings and the other with sleep onset latency at 10 months as the outcome variable. In both models, TSI and ASD likelihood status were entered as predictors. TSI had a significant effect on sleep onset latency (Waldχ 2 = 7.775, p = 0.005), but not on the number of awakenings (Waldχ 2 = 0.009, p = 0.923), see Fig. 3. ASD likelihood status did not have a significant effect on awakenings at 10 months (Waldχ 2 = 2.616, p = 0.106) and there was also no significant effect of the the interaction between ASD likelihood status and TSI (Waldχ 2 = 1.146, p = 0.284). ASD likelihood status did not have a significant effect (Waldχ 2 = 2.125, p = 0.145) nor did it significantly interact with TSI (Waldχ 2 = 0.284, p = 0.594) in predicting sleep onset latency at 10 months.  To evaluate if TSI at 10 months associates longitudinally with the sleep parameters at 14 months, over and above 10-month sleep, separate models were run with 14-month sleep onset latency or number of awakenings as outcomes. In both models TSI, ASD likelihood status and the relevant 10-month sleep measure (onset latency/number of awakenings), were entered as predictors. TSI did not significantly associate with the number of awakenings (Waldχ 2 = 0.128, p = 0.721) or sleep onset latency at 14 months (Waldχ 2 = 0.635, p = 0.425). The results remained substantively similar when the models were re-run excluding the EL-ASD + participants (n = 5), suggesting that these infants did not drive the results in the main analysis and that the association between TSI and sleep is not specific to ASD (see Table S6 and S7).

Discussion
Characterising sleep trajectories of infants at TL and EL for ASD revealed that sleep onset latency and night awakenings decrease in infants at TL from 5 to 14 months. These patterns mirror previous findings that sleep consolidates during the first year of life in typically developing infants 40 . In contrast, no developmental change was seen in infants at EL, leading to significant differences between the groups from 10 months, with longer sleep onset latency and more night awakenings in infants at EL than TL. Further, our results show that an objective measure of poor sensory gating of tactile stimulation significantly associates with longer sleep onset latency. This finding was independent of ASD likelihood status, implying that there is a general association between sensory gating and sleep onset latency, in line with previous evidence in typically developing children 37 . No association between sensory gating and number of night awakenings was found, either suggesting a differential mechanism of sensory gating during pre-sleep wake and sleep itself or simply reflecting unreliable caregiver reports of night awakenings compared to sleep onset latency. We discuss each of these findings in turn, below.
Trajectories of sleep parameters. In a previous paper, using the same cohort of children, we reported that a composite score of night sleep was worse in infants at EL compared to infants at TL at 5, 10 and 14 months 4 . Here, we specifically focused on two measures of sleep expected to be influenced by the ability to gate sensory input-sleep onset latency and night awakenings. Our findings suggest differences in both of these parameters emerge between 5 and 10 months, which narrows down the developmental interval within which to investigate underlying causes. Using a less precise measure, asking about the presence of frequent night awakenings (3 or more) and not the exact number awakenings, in a longitudinal population study, Humphreys et al. 41 only found a significant difference in frequent night awakenings between TD and ASD at 30 months, but not at 6 or 18 months. In our sample, however, infants at EL woke up more frequently than infants at TL from 10 months, suggesting an earlier emergence.
Subdividing the EL infants into infants that were or were not subsequently diagnosed with ASD (EL-ASD + and EL-ASD-respectively) showed that infants at EL-ASD + took longest to fall asleep, suggesting that sleep onset latency is intrinsically driven in infants at EL for ASD, rather than a result of a shared environment with an older sibling with ASD. The differences in night awakening trajectories between infants at EL-ASD + and EL-ASD-were less consistent, likely due to the small sample sizes in the subgroups. Further research is needed to investigate these differences in infants at EL-ASD + and EL-ASD-. The impact of sensory gating on sleep. The fact that reduced sensory gating was associated with longer sleep onset latency, but not with more night awakenings is consistent with literature suggesting these sleep processes have different underlying mechanisms. For example, adults with sleep onset problems, showed reduced repetition suppression to auditory stimuli during pre-sleep wake compared to good sleepers, but not during rapid eye movement (REM) or non REM2 (N2) 42 . In support of different neural mechanisms underlying sleep onset and maintenance, the manipulation of the inhibitory neurotransmitter GABA A receptor, which has an important role in sleep 43 , affected sleep initiation more than sleep maintenance in fruit flies 44 . In adult patients with primary insomnia (PI), auditory stimulation did not increase the number of awakenings compared to an undisturbed, baseline night sleep. However, the PI group was more likely to stay in REM sleep when stimulation occurred while controls transitioned to N2 more often 45 . Thus, while increased stimulus input (due to poor gating) might not result in more awakenings, it might still affect sleep quality and architecture to a larger extent in populations with sleep difficulties, like in ASD. The incongruity of the reported association between sensory gating and sleep onset latency but not awakenings might also reflect the nature of the sensory gating measure used in this study. Sensory gating was measured during wakefulness and might therefore be more closely related to arousibility at sleep onset compared to arousibility from sleep. Kisley et al. 46 reported differences in sensory gating, although in response to auditory stimulation, dependent on vigilance state in the same individuals. Alternatively, the discrepancy in our findings between awakenings and sleep onset latency could be caused by the accuracy of caregiver report. Sadeh et al. 47 found that parents reported the number of awakenings significantly less accurately than sleep onset in infants when compared with actigraphy results. Moreover, Pisch et al. 48 found no significant association between parent reported awakenings and actigraphy in infants. The association we find between tactile repetition suppression and sleep onset latency is indicative of common underlying mechanisms. One possibility is that impaired GABAergic functioning impacts both sensory gating and sleep. GABA is the main inhibitory neurotransmitter in the brain. Altered functioning of GABAergic signaling in ASD is evident from lower GABA levels, reduced expression of GABAergic genes and microdeletion in genes coding for subunits of the GABA A receptor 49 . Both sensory processing atypicalities and sleep onset problems could be triggered by reduced GABA levels. In fact, sleep onset latency was decreased in rats after oral administration of GABA 50 , and mutation of GABA A -receptor in fruit flies resulted in a reduction of sleep onset latency 44 . At the same time, Puts et al. 51 found that reduced sensorimotor GABA-levels in children with ASD are associated with sensitivity to touch. Thus, an impaired GABA-ergic system could underlie the co-occurrence of sensory issues and sleep disturbances in ASD. In general, there is accumulating evidence to believe that an exitation/inhibition (E/I) imbalance, particularly relevant during brain development, plays an important role in the pathophysiology of ASD. Besides affecting basic sensory processing and sleep, an E/I imbalance disturbs optimal information transmission, which could alter processing of complex information such as social stimuli, resulting in social and cognitive impairments seen in ASD.
Another possibility is that atypical thalamocortical connectivity underlies both sensory and sleep problems in ASD. A recent paper found that increased sleep latency was associated with increased thalamocortical connectivity, as well as elevated BOLD activity in the cortex in children with ASD 52 .
Longitudinal effects of sensory gating. TL participants showed a further decrease in sleep onset latency between 10 and 14 months. These changes may, in part, reflect the development of self-soothing strategies. The mechanisms driving individual progress in self-soothing are poorly understood, but it is believed this requires infants to identify body cues for sleepiness and to use behavioral strategies, such as sucking on fingers, to fall asleep more easily 53,54 . It is therefore plausible that poor sensory gating may not only delay sleep onset but it may also interfere with the development of these strategies. We found tactile repetition suppression did not predict sleep onset latency at 14 months after controlling for 10-month sleep onset latency. This suggests that the effects of reduced sensory gating on sleep do not accumulate over time. Manelis-Baram et al. 55 found that changes in sleep disturbances between 3 and 5 years of age were associated with changes in sensory sensitivities specifically, and not with other core ASD symptoms, in autistic children. Similar to our results, they found that initial sensory profile scores did not predict sleep disturbances at a later timepoint. The absence of long lasting impacts on sleep suggest that addressing sensory issues for interventions could therefore be an effective strategy at any age.
ASD is a complex, multifaceted disorder, with sleep problems, which are equally diverse in ASD as the disorder itself, and that likely originate from multiple pathways. Our findings support one of those pathways, however other underlying mechanisms most likely contribute to sleep and sleep onset problems in ASD. Differences in melatonin production, clock gene expression and behavioural complications such as the high prevalence of anxiety that is associated with ASD, have all been suggested as contributory factors to sleep problems 22 .
While this study is novel in its use of an objective measure for sensory gating, sleep is captured by caregiver reports and not by more objective measures. The use of actigraphy or polysomnography could greatly improve the reliability of sleep behaviours, particularly for night awakenings.
Given the critical role of sleep to development, our finding that diminished tactile repetition suppression is associated with prolonged sleep onset has important clinical implications. While atypical sensory gating in infants at EL for ASD is not specific to the tactile domain 33 , tactile input may be particularly prominent before and during sleep compared to sensory input from other modalities. Visual input can be reduced by turning off the lights and auditory input by closing a door; in contrast, infants will experience continuous tactile input, especially when moving around in bed. This suggests that interventions which target tactile input to improve sleep may be particularly fruitful. An encouraging first step was made by a study showing that sleep quality improved in a group of children with sensory processing disorder that received a massage before bedtime 56 . Since both sensory atypicalities and sleep disturbances are common in the early development of ASD, early interventions

Data availability
At present, the datasets generated and/or analysed during the current study are not publicly available due to confidentiality constraints within our ethical approvals. In the future, we hope to make these datasets available via The BASIS Network (http:// www. basis netwo rk. org/) upon completion of the requisite data access and sharing protocols.